Back to Search Start Over

Computing wide range of protein/peptide features from their sequence and structure

Authors :
Rajesh Kumar
Akshara Pande
Chakit Arora
Gajendra P. S. Raghava
Piyush Agrawal
Neelam Sharma
Anjali Dhall
Gaurav Mishra
Salman Sadullah Usmani
Anjali Lathwal
Kumar
Sumeet Patiyal
Shipra Jain
Harpreet Kaur
Dilraj Kaur
Publication Year :
2019
Publisher :
Cold Spring Harbor Laboratory, 2019.

Abstract

MotivationIn last three decades, a wide range of protein descriptors/features have been discovered to annotate a protein with high precision. A wide range of features have been integrated in numerous software packages (e.g., PROFEAT, PyBioMed, iFeature, protr, Rcpi, propy) to predict function of a protein. These features are not suitable to predict function of a protein at residue level such as prediction of ligand binding residues, DNA interacting residues, post translational modification etc.ResultsIn order to facilitate scientific community, we have developed a software package that computes more than 50,000 features, important for predicting function of a protein and its residues. It has five major modules for computing; composition-based features, binary profiles, evolutionary information, structure-based features and patterns. The composition-based module allows user to compute; i) simple compositions like amino acid, dipeptide, tripeptide; ii) Properties based compositions; iii) Repeats and distribution of amino acids; iv) Shannon entropy to measure the low complexity regions; iv) Miscellaneous compositions like pseudo amino acid, autocorrelation, conjoint triad, quasi-sequence order. Binary profile of amino acid sequences provides complete information including order of residues or type of residues; specifically, suitable to predict function of a protein at residue level. Pfeature allows one to compute evolutionary information-based features in form of PSSM profile generated using PSIBLAST. Structure based module allows computing structure-based features, specifically suitable to annotate chemically modified peptides/proteins. Pfeature also allows generating overlapping patterns and feature from whole protein or its parts (e.g., N-terminal, C-terminal). In summary, Pfeature comprises of almost all features used till now, for predicting function of a protein/peptide including its residues.AvailabilityIt is available in form of a web server, named as Pfeature (https://webs.iiitd.edu.in/raghava/pfeature/), as well as python library and standalone package (https://github.com/raghavagps/Pfeature) suitable for Windows, Ubuntu, Fedora, MacOS and Centos based operating system.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....96240720bc1511229f759d1081f72cf1
Full Text :
https://doi.org/10.1101/599126